The gap between demo and reliable ROI | Pratik Verma

About this episode

Your AI agent nailed the demo. But two weeks after going live, you're staring at support tickets you can't reproduce, cloud bills you can't explain, and behavior nobody predicted.

In this episode of Particle Accelerator, our host Benjamin Johnson sits down with Pratik Verma, Founder and CEO of Okahu AI, to unpack exactly why AI agents break in production and what it takes to actually build reliable, observable agentic systems. Pratik has spent years at Microsoft and leading his own AI infrastructure companies. His open-source Monocle library and Okahu platform are purpose-built for the era of non-deterministic, LLM-powered agents, filling the gap that Datadog, New Relic, and traditional APM tools simply weren't designed for.

In this conversation, Benjamin and Pratik get into:

The most common root cause of agent failure (hint: it's not the model)

Why the orchestration layer is where everything breaks

Real-world example, how an Epson QA team cut triage from 30 hrs to 2 hrs with agents

The structural difference between tracing a microservice vs. tracing an agent
Evals vs. observability, what they are, why you need both, and how they connect

How to instrument for token cost waste from day one

MCP observability, what happens when you can't see inside the calling agent

The self-healing agent loop, observability, coding agent, fix and repeat

What software engineering looks like in 3 years

Chapters: 
00:00 - Intro & Guest Welcome
01:05 - Why agents fail: lab vs. production reality
02:28 - The orchestration layer: where flexibility becomes fragility
04:00 - The noun confusion failure mode (real-world example)
04:51 - The failure mode engineering leaders never see coming
06:29 - Why Datadog doesn't work for AI agents
11:22 - Instrumenting for cost: token budgets, session tracking & alerts
14:22 - Evals vs. observability: drawing the line
17:21 - From deterministic to non-deterministic systems
18:24 - Real-world case study: Epson QA agents
22:51 - Call center AI & observability signals in practice
30:07 - MCP observability and institutional knowledge loops
35:10 - The emerging agent economy and skill repositories
46:26 - What the next 3 years of AI looks like

Pratik Verma, Founder & CEO, Okahu AI
Connect with him: https://www.linkedin.com/in/pratikrverma/
Learn more at: https://www.okahu.ai/

Benjamin Johnson, Host, Particle Accelerator & CEO, Particle41
Connect with Benjamin on LinkedIn: https://www.linkedin.com/in/benjaminrjohnson/ 

Learn more about Particle41: https://particle41.com/

#AIAgents #MLOps #AIObservability #ProductionAI #EngineeringLeadership #TheParticleAccelerator #Particle41